Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	18,466
2	New Jersey	16,932
3	Massachusetts	12,908
4	Rhode Island	12,607
5	Connecticut	10,943
6	District of Columbia	10,699
7	Delaware	8,414
8	Illinois	7,947
9	Louisiana	7,623
10	Maryland	7,020
11	Nebraska	5,749
12	Pennsylvania	5,323
13	Michigan	5,305
14	Iowa	5,029
15	South Dakota	4,721
16	Indiana	4,454
17	Mississippi	4,020
18	Colorado	3,953
19	Virginia	3,855
20	Georgia	3,594
21	Minnesota	3,134
22	New Mexico	3,022
23	Kansas	2,972
24	New Hampshire	2,844
25	North Dakota	2,749
26	Tennessee	2,713
27	Alabama	2,661
28	Washington	2,649
29	Ohio	2,518
30	Utah	2,407
31	Nevada	2,370
32	Wisconsin	2,331
33	Florida	2,209
34	California	2,179
35	Arizona	2,046
36	North Carolina	1,927
37	Missouri	1,875
38	Kentucky	1,865
39	Texas	1,799
40	South Carolina	1,781
41	Arkansas	1,657
42	Vermont	1,512
43	Idaho	1,402
44	Oklahoma	1,398
45	Wyoming	1,359
46	Maine	1,353
47	Oregon	901
48	Puerto Rico	897
49	West Virginia	874
50	Alaska	549
51	Hawaii	447
52	Montana	447

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Rhode Island	214
2	District of Columbia	202
3	Maryland	194
4	Delaware	179
5	Illinois	167
6	New Jersey	152
7	Connecticut	149
8	Massachusetts	143
9	Nebraska	133
10	Iowa	128
11	Minnesota	118
12	Virginia	98
13	Alabama	87
14	North Dakota	85
15	Indiana	77
16	Mississippi	75
17	New York	71
18	South Dakota	71
19	Georgia	69
20	Kansas	67
21	Louisiana	67
22	New Hampshire	66
23	Michigan	64
24	New Mexico	63
25	Pennsylvania	62
26	Wisconsin	57
27	Tennessee	55
28	North Carolina	53
29	Colorado	49
30	Utah	49
31	California	48
32	Arizona	43
33	Ohio	43
34	Kentucky	40
35	Nevada	39
36	Texas	38
37	Maine	32
38	Florida	29
39	Arkansas	26
40	Washington	25
41	Missouri	23
42	South Carolina	23
43	Puerto Rico	22
44	Wyoming	19
45	Oklahoma	18
46	Idaho	15
47	Oregon	14
48	West Virginia	13
49	Montana	3
50	Alaska	2
51	Vermont	2
52	Hawaii	0

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	1,467
2	New Jersey	1,209
3	Connecticut	989
4	Massachusetts	880
5	District of Columbia	576
6	Louisiana	561
7	Rhode Island	507
8	Michigan	506
9	Pennsylvania	374
10	Illinois	358
11	Maryland	351
12	Delaware	318
13	Indiana	276
14	Colorado	225
15	Mississippi	191
16	Georgia	157
17	Ohio	152
18	Minnesota	139
19	New Hampshire	139
20	Washington	137
21	New Mexico	134
22	Iowa	126
23	Virginia	125
24	Nevada	122
25	Alabama	106
26	Missouri	105
27	Arizona	102
28	Florida	97
29	California	88
30	Vermont	86
31	Kentucky	85
32	Wisconsin	82
33	South Carolina	79
34	Oklahoma	75
35	Nebraska	72
36	North Carolina	68
37	Kansas	67
38	North Dakota	64
39	Maine	54
40	South Dakota	51
41	Texas	49
42	Tennessee	45
43	Idaho	43
44	Puerto Rico	39
45	West Virginia	38
46	Arkansas	35
47	Oregon	34
48	Utah	28
49	Wyoming	19
50	Montana	14
51	Hawaii	12
52	Alaska	10

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	New Jersey	14
2	Massachusetts	13
3	Rhode Island	12
4	Connecticut	11
5	District of Columbia	11
6	Illinois	9
7	Louisiana	8
8	Maryland	7
9	Pennsylvania	7
10	Delaware	6
11	New York	6
12	Indiana	5
13	Iowa	5
14	Michigan	5
15	Mississippi	5
16	Colorado	4
17	New Hampshire	4
18	Ohio	4
19	Arizona	3
20	Minnesota	3
21	Nevada	3
22	Alabama	2
23	Georgia	2
24	Kentucky	2
25	Missouri	2
26	Nebraska	2
27	New Mexico	2
28	North Dakota	2
29	Virginia	2
30	California	1
31	Florida	1
32	North Carolina	1
33	South Carolina	1
34	Utah	1
35	Washington	1
36	Wisconsin	1
37	Wyoming	1
38	Alaska	0
39	Arkansas	0
40	Hawaii	0
41	Idaho	0
42	Kansas	0
43	Maine	0
44	Montana	0
45	Oklahoma	0
46	Oregon	0
47	Puerto Rico	0
48	South Dakota	0
49	Tennessee	0
50	Texas	0
51	Vermont	0
52	West Virginia	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	122,652	1	99
Dakota	Nebraska	78,698	2	99
Lincoln	Arkansas	74,171	3	99
Nobles	Minnesota	64,543	4	99
Lake	Tennessee	57,440	5	99
Davidson	Tennessee	6,489	245	92
Richland	South Carolina	3,096	617	80
Pierce	Washington	2,029	913	70
Orange	California	1,494	1175	62
York	South Carolina	1,128	1431	54

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Randolph	Georgia	3,098	1	99
Early	Georgia	2,846	2	99
Terrell	Georgia	2,813	3	99
Essex	New Jersey	1,964	4	99
Nassau	New York	1,879	5	99
Richland	South Carolina	149	535	82
Pierce	Washington	78	820	73
Davidson	Tennessee	72	858	72
Orange	California	31	1270	59
York	South Carolina	18	1482	52

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.